Sowing date, genotype choice, and water environment control soybean yields in central Argentina

Autores
Vitantonio Mazzini, Lucas Nicolás; Gómez, Damián; Gambin, Brenda Laura; Di Mauro, Guido; Iglesias, Rodrigo; Costanzi, Jerónimo; Jobbágy, Esteban G.; Borras, Lucas
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Soybean [Glycine max (L.) Merr.] is one of the most important crops worldwide, and Argentina is the third largest global grain producer and the worlds´ largest meal exporter. Under the continuous challenge of increasing crop yields, especially in the central temperate region of the country, there is a growing need to optimize management in relation to the environment that each specific farm and paddock presents. Understanding the impact of available technologies and management options can help optimize crop design. Here, we identify and quantify the effect of the most relevant variables affecting soybean yield by analyzing a database that includes 53 field trials with four common commercial genotypes, reporting 50 management and environmental variables. Linear mixed-effect models revealed that two management decisions (genotype and sowing date selection) and three environmental variables (rainfall during the reproductive crop period from R1 to R7, soil type [Hapludoll vs. Argiudoll], and water table presence above or below 2 m of depth from the surface) helped explain ∼40% of total yield variability, which ranged from 1,675 to 7,226 kg ha−1 and averaged 5,133 kg ha−1. Water table presence generated higher and more stable yields particularly in coarse-textured Hapludolls and under low-rainfall conditions. Results highlight specific management and environmental conditions that affect soybean crop yields in the region, pointing to effective pathways toward yield gap reductions.
Fil: Vitantonio Mazzini, Lucas Nicolás. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
Fil: Gómez, Damián. Don Mario; Argentina
Fil: Gambin, Brenda Laura. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina
Fil: Di Mauro, Guido. Don Mario; Argentina
Fil: Iglesias, Rodrigo. Don Mario; Argentina
Fil: Costanzi, Jerónimo. Don Mario; Argentina
Fil: Jobbágy, Esteban G.. Universidad Nacional de San Luis; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentina
Fil: Borras, Lucas. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
Materia
soybean
yield
predicting yield
sowing date
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/184587
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/184587
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Sowing date, genotype choice, and water environment control soybean yields in central ArgentinaVitantonio Mazzini, Lucas NicolásGómez, DamiánGambin, Brenda LauraDi Mauro, GuidoIglesias, RodrigoCostanzi, JerónimoJobbágy, Esteban G.Borras, Lucassoybeanyieldpredicting yieldsowing datehttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4Soybean [Glycine max (L.) Merr.] is one of the most important crops worldwide, and Argentina is the third largest global grain producer and the worlds´ largest meal exporter. Under the continuous challenge of increasing crop yields, especially in the central temperate region of the country, there is a growing need to optimize management in relation to the environment that each specific farm and paddock presents. Understanding the impact of available technologies and management options can help optimize crop design. Here, we identify and quantify the effect of the most relevant variables affecting soybean yield by analyzing a database that includes 53 field trials with four common commercial genotypes, reporting 50 management and environmental variables. Linear mixed-effect models revealed that two management decisions (genotype and sowing date selection) and three environmental variables (rainfall during the reproductive crop period from R1 to R7, soil type [Hapludoll vs. Argiudoll], and water table presence above or below 2 m of depth from the surface) helped explain ∼40% of total yield variability, which ranged from 1,675 to 7,226 kg ha−1 and averaged 5,133 kg ha−1. Water table presence generated higher and more stable yields particularly in coarse-textured Hapludolls and under low-rainfall conditions. Results highlight specific management and environmental conditions that affect soybean crop yields in the region, pointing to effective pathways toward yield gap reductions.Fil: Vitantonio Mazzini, Lucas Nicolás. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; ArgentinaFil: Gómez, Damián. Don Mario; ArgentinaFil: Gambin, Brenda Laura. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; ArgentinaFil: Di Mauro, Guido. Don Mario; ArgentinaFil: Iglesias, Rodrigo. Don Mario; ArgentinaFil: Costanzi, Jerónimo. Don Mario; ArgentinaFil: Jobbágy, Esteban G.. Universidad Nacional de San Luis; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; ArgentinaFil: Borras, Lucas. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; ArgentinaCrop Science Society of America2020-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/184587Vitantonio Mazzini, Lucas Nicolás; Gómez, Damián; Gambin, Brenda Laura; Di Mauro, Guido; Iglesias, Rodrigo; et al.; Sowing date, genotype choice, and water environment control soybean yields in central Argentina; Crop Science Society of America; Crop Science; 61; 1; 8-2020; 715-7280011-183XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/csc2.20315info:eu-repo/semantics/altIdentifier/doi/10.1002/csc2.20315info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:45:57Zoai:ri.conicet.gov.ar:11336/184587instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:45:57.403CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Sowing date, genotype choice, and water environment control soybean yields in central Argentina
title Sowing date, genotype choice, and water environment control soybean yields in central Argentina
spellingShingle Sowing date, genotype choice, and water environment control soybean yields in central Argentina
Vitantonio Mazzini, Lucas Nicolás
soybean
yield
predicting yield
sowing date
title_short Sowing date, genotype choice, and water environment control soybean yields in central Argentina
title_full Sowing date, genotype choice, and water environment control soybean yields in central Argentina
title_fullStr Sowing date, genotype choice, and water environment control soybean yields in central Argentina
title_full_unstemmed Sowing date, genotype choice, and water environment control soybean yields in central Argentina
title_sort Sowing date, genotype choice, and water environment control soybean yields in central Argentina
dc.creator.none.fl_str_mv Vitantonio Mazzini, Lucas Nicolás
Gómez, Damián
Gambin, Brenda Laura
Di Mauro, Guido
Iglesias, Rodrigo
Costanzi, Jerónimo
Jobbágy, Esteban G.
Borras, Lucas
author Vitantonio Mazzini, Lucas Nicolás
author_facet Vitantonio Mazzini, Lucas Nicolás
Gómez, Damián
Gambin, Brenda Laura
Di Mauro, Guido
Iglesias, Rodrigo
Costanzi, Jerónimo
Jobbágy, Esteban G.
Borras, Lucas
author_role author
author2 Gómez, Damián
Gambin, Brenda Laura
Di Mauro, Guido
Iglesias, Rodrigo
Costanzi, Jerónimo
Jobbágy, Esteban G.
Borras, Lucas
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv soybean
yield
predicting yield
sowing date
topic soybean
yield
predicting yield
sowing date
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Soybean [Glycine max (L.) Merr.] is one of the most important crops worldwide, and Argentina is the third largest global grain producer and the worlds´ largest meal exporter. Under the continuous challenge of increasing crop yields, especially in the central temperate region of the country, there is a growing need to optimize management in relation to the environment that each specific farm and paddock presents. Understanding the impact of available technologies and management options can help optimize crop design. Here, we identify and quantify the effect of the most relevant variables affecting soybean yield by analyzing a database that includes 53 field trials with four common commercial genotypes, reporting 50 management and environmental variables. Linear mixed-effect models revealed that two management decisions (genotype and sowing date selection) and three environmental variables (rainfall during the reproductive crop period from R1 to R7, soil type [Hapludoll vs. Argiudoll], and water table presence above or below 2 m of depth from the surface) helped explain ∼40% of total yield variability, which ranged from 1,675 to 7,226 kg ha−1 and averaged 5,133 kg ha−1. Water table presence generated higher and more stable yields particularly in coarse-textured Hapludolls and under low-rainfall conditions. Results highlight specific management and environmental conditions that affect soybean crop yields in the region, pointing to effective pathways toward yield gap reductions.
Fil: Vitantonio Mazzini, Lucas Nicolás. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
Fil: Gómez, Damián. Don Mario; Argentina
Fil: Gambin, Brenda Laura. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina
Fil: Di Mauro, Guido. Don Mario; Argentina
Fil: Iglesias, Rodrigo. Don Mario; Argentina
Fil: Costanzi, Jerónimo. Don Mario; Argentina
Fil: Jobbágy, Esteban G.. Universidad Nacional de San Luis; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentina
Fil: Borras, Lucas. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Cátedra de Cultivo Extensivos Cereales y Oleaginosas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina
description Soybean [Glycine max (L.) Merr.] is one of the most important crops worldwide, and Argentina is the third largest global grain producer and the worlds´ largest meal exporter. Under the continuous challenge of increasing crop yields, especially in the central temperate region of the country, there is a growing need to optimize management in relation to the environment that each specific farm and paddock presents. Understanding the impact of available technologies and management options can help optimize crop design. Here, we identify and quantify the effect of the most relevant variables affecting soybean yield by analyzing a database that includes 53 field trials with four common commercial genotypes, reporting 50 management and environmental variables. Linear mixed-effect models revealed that two management decisions (genotype and sowing date selection) and three environmental variables (rainfall during the reproductive crop period from R1 to R7, soil type [Hapludoll vs. Argiudoll], and water table presence above or below 2 m of depth from the surface) helped explain ∼40% of total yield variability, which ranged from 1,675 to 7,226 kg ha−1 and averaged 5,133 kg ha−1. Water table presence generated higher and more stable yields particularly in coarse-textured Hapludolls and under low-rainfall conditions. Results highlight specific management and environmental conditions that affect soybean crop yields in the region, pointing to effective pathways toward yield gap reductions.
publishDate 2020
dc.date.none.fl_str_mv 2020-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/184587
Vitantonio Mazzini, Lucas Nicolás; Gómez, Damián; Gambin, Brenda Laura; Di Mauro, Guido; Iglesias, Rodrigo; et al.; Sowing date, genotype choice, and water environment control soybean yields in central Argentina; Crop Science Society of America; Crop Science; 61; 1; 8-2020; 715-728
0011-183X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/184587
identifier_str_mv Vitantonio Mazzini, Lucas Nicolás; Gómez, Damián; Gambin, Brenda Laura; Di Mauro, Guido; Iglesias, Rodrigo; et al.; Sowing date, genotype choice, and water environment control soybean yields in central Argentina; Crop Science Society of America; Crop Science; 61; 1; 8-2020; 715-728
0011-183X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/abs/10.1002/csc2.20315
info:eu-repo/semantics/altIdentifier/doi/10.1002/csc2.20315
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Crop Science Society of America
publisher.none.fl_str_mv Crop Science Society of America
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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